US7890517B2 - Appliance for enterprise information integration and enterprise resource interoperability platform and methods - Google Patents
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- US7890517B2 US7890517B2 US11/064,438 US6443805A US7890517B2 US 7890517 B2 US7890517 B2 US 7890517B2 US 6443805 A US6443805 A US 6443805A US 7890517 B2 US7890517 B2 US 7890517B2
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Definitions
- the teachings of all of the foregoing application and patents are incorporated herein by reference.
- the invention pertains to digital data processing and, specifically, to apparatus providing platforms and methods for enterprise information integration (EII) and enterprise resource interoperability (ERI), and methods of using those apparatus for that purpose.
- EII enterprise information integration
- ERP enterprise resource interoperability
- the invention has application in public health & bioterrorism, border and port security, public and community safety, and (state and local) government data integration, the travel & transportation industry, and the financial services industry, to name a few.
- system clusters Each of these clusters—sometimes called “stovepipes”—contains multiple applications, databases, servers, storage devices, and network infrastructure. Each is typically allocated to a specific business unit, cost center, or division—that is, a cluster is bought and paid for out of a specific budget and its resources are devoted to a specific business function (e.g., finance has its own systems and manufacturing has its own separate systems).
- system clusters sometimes called “stovepipes”—contains multiple applications, databases, servers, storage devices, and network infrastructure.
- Each is typically allocated to a specific business unit, cost center, or division—that is, a cluster is bought and paid for out of a specific budget and its resources are devoted to a specific business function (e.g., finance has its own systems and manufacturing has its own separate systems).
- finance has its own systems and manufacturing has its own separate systems
- the Centers for Disease Control and Prevention (CDC) of the U.S. Department of Health and Human Services has launched several initiatives toward forming nation-wide networks of shared health-related information that, when fully implemented, will facilitate the rapid identification of, and response to, health and bioterrorism threats.
- the CDC plans the Health Alert Network (HAN), for example, to provide infrastructure supporting for distribution of health alerts, disease surveillance, and laboratory reporting.
- HAN Health Alert Network
- PIN Public Health Information Network
- PIN is another CDC initiative that will provide detailed specifications for the acquisition, management, analysis and dissemination of health-related information, building upon the HAN and other CDC initiatives, such as the National Electronic Disease Surveillance System (NEDSS).
- An object of this invention is to provide improved methods and platforms for enterprise information (EII) integration and enterprise resource interoperability (ERI).
- EII enterprise information
- ERP enterprise resource interoperability
- a related object is to provide such methods and platforms as can be applied across a range of industries, from public health & bioterrorism, border and port security, public and community safety, and (state and local) government data integration, the travel & transportation industry, and the financial services industry, to name a few.
- a further object of the invention is to provide apparatus for effecting ready installation and integration of the aforementioned methods and platforms in an enterprise.
- Gray matter regions of the central nervous system, the brain, and spinal cord are the areas where the actual “processing” is performed.
- the white matter provides the communication among different gray matter areas and between the gray matter and the rest of the body.
- the gray matter is where the processing is done and the white matter is the channels of communication between the gray matter units.
- gray matter is like the individual systems that run within an enterprise and the white matter is the communication network that ties them together and leverages all the systems as if they were one.
- White Matter Computing as a term to describe the communications, collaboration, and coordination among various applications, information systems, and data stores.
- grid computing enables virtual organizations to share geographically dispersed resources as they pursue common goals. Tying together disparate hardware is an essential first step in grid computing. You want to leverage all available CPU cycles, memory, and storage to their fullest.
- Information grids preserve and resolve the semantic distinctions among disparate sources of data and content. Whereas data grids merely provide universal access, an information grid unifies the information itself, while it remains across multiple, disparate information domains (such as applications, databases, infrastructure, and networks).
- an enterprise information grid is conceptual, not physical. Therefore, it can be deployed with or without a physical grid infrastructure (i.e. computational grid, storage grid, or data grid).
- a physical grid infrastructure i.e. computational grid, storage grid, or data grid.
- Apparatus, platforms and methods according to the invention use the W3C's Resource Description Framework (RDF) standard—a model and syntax for representing metadata as part of the global information model. That enables apparatus, platforms and methods according to the invention to accommodate data in any form: structured, semi-structured, or unstructured.
- RDF Resource Description Framework
- apparatus, platforms and methods according to the invention provide a surveillance, monitoring and real-time events platform to (i) enable the integration and communication of information between government agencies and organizations specifically tasked with ensuring the security and safety of our nation and its communities, (ii) to integrate information systems from federal, state and/or local agencies (from disparate data sources if necessary) in order to obtain a single, real-time view of the entire organization, and (iii) to extract more complete, actionable information from their existing systems, thereby dramatically improving decision making speed and accuracy.
- the platform has application in a variety of areas, including, public health & bioterrorism, border and port security, public and community safety, government data integration, the travel and transportation industry, and the financial services industry, to name a few.
- the surveillance, monitoring and real-time events platform is adapted for use, e.g., as a local, state or federal node, in a network conforming to the Public Health Information Network (PHIN) initiative of the Centers for Disease Control and Prevention (CDC) of the U.S. Department of Health and Human Services, or as an infrastructure element of that network.
- PIN Public Health Information Network
- CDC Centers for Disease Control and Prevention
- Systems and methods according to this aspect of the invention are designed as for multipurposes. They function as a real-time surveillance system, a bioterrorism detection and response system and a collaborative network for distance learning and communication.
- Border and port security represent complex security challenges. These sites represent vulnerable points of entry and require monitoring of ocean vessel arrivals and departures, assessing potentially hazardous cargo, responding to immigration challenges, terrorist threats and managing the proximity risk to civilians and land-based targets such as nuclear facilities, dams, power plants, gas lines, and other biological and chemical facilities. Due to the complex and porous nature of borders and ports, many distinct organizations are required to work in close cooperation and effectively share critical information.
- the surveillance, monitoring and real-time events plat-form is adapted for border and port security applications, providing:
- the surveillance, monitoring and real-time events platform can be deployed in applications designed to identify community threats or security breaches in a wide range of settings including inter-agency solutions for superior security surveillance and response. This platform provides:
- the surveillance, monitoring and real-time events plat-form provides a single point of access to all state security-related IT systems (Justice Dept, Law Enforcement, Dept of Health) to expedite identifying potential threats.
- the platform can also provide information visibility across an organizations systems. The platform:
- apparatus e.g., a server/application appliance
- apparatus e.g., a server/application appliance
- apparatus that facilitate quick and easy connections to and integration with any data source, integrate with data sources, as well as to generate alerts, reports and other information from those sources, in real-time.
- FIG. 1 depicts advantages of Eli and ERI systems according to the invention from a data perspective and an enterprise-wide resource perspective;
- FIG. 2 depicts a relationship between enterprise application integration (EAI), EII, distributed EII (D-EII) and ERI.
- EAI enterprise application integration
- EII distributed EII
- ERI ERI
- FIG. 3 depicts the components and interrelationships of a grid-based ERI platform according to the invention.
- FIG. 4 depicts a relationship between raw data (e.g., as stored in SQL, DB 2 and Oracle databases), knowledge and intelligence (e.g., as supported by a distributed ERI platform according to the invention) and user interaction (e.g., as supported by GUIs of “white matter” applications).
- the figure also depicts a relationship between information services applications, interoperability services, and the distributed ERI platform according to the invention.
- the figure depicts a relationship between enterprise resources, the distributed ERI plat-form according to the invention, ERI applications executing thereon, and a service oriented architecture (SOA).
- SOA service oriented architecture
- FIG. 5 depicts a surveillance, monitoring and real-time events system according to the invention suitable for the adaptation to a public health & bioterrorism application, e.g., as part of PHIN, HAN or NEDSS-compatible networks;
- FIG. 6 depicts the system of FIG. 5 that further utilizes a server/application appliance according to the invention.
- FIGS. 7-19 depict a visual display used in the system of FIG. 1 to call alerts and other information to the attention of the user.
- FIG. 20 depicts an expert engine according to one practice of the invention.
- FIG. 1 depicts advantages of EII and ERI systems according to the invention from a data perspective and an enterprise-wide resource perspective.
- FIG. 2 depicts a relationship between enterprise application integration (EAI), EII, distributed EII (D-EII) and ERI.
- EAI enterprise application integration
- EII distributed EII
- ERI ERI
- FIG. 3 depicts the components and interrelationships of a grid-based ERI platform according to the invention.
- FIG. 4 depicts a relationship between raw data (e.g., as stored in SQL, DB 2 and Oracle databases), knowledge and intelligence (e.g., as supported by a distributed ERI platform according to the invention) and user interaction (e.g., as supported by GUIs of “white matter” applications).
- the figure also depicts a relationship between information services applications, interoperability services, and the distributed ERI platform according to the invention.
- the figure depicts a relationship between enterprise resources, the distributed ERI plat-form according to the invention, ERI applications executing thereon, and a service oriented architecture (SOA).
- SOA service oriented architecture
- FIG. 5 depicts a surveillance, monitoring and real-time events system 100 of the type supported by platforms and systems according to the invention suitable for the adaptation to a public health & bioterrorism application, e.g., as part of PHIN, HAN or NEDSS networks.
- Illustrated system 100 represents a data processing station (or stations) resident at a node in such a network, such as, for example, a clinical care provider, a laboratory, a local or state health department, the CDC headquarters, a local or national law enforcement office, or other-wise.
- a data processing station or stations resident at a node in such a network, such as, for example, a clinical care provider, a laboratory, a local or state health department, the CDC headquarters, a local or national law enforcement office, or other-wise.
- the illustrated system is used in a public health & bioterrorism application, it will be appreciated that a similar such system can be applied in border & port security, public & community safety, and government data integration applications, described above,
- Illustrated system 100 which can be embodied in conventional digital data processing apparatus (including attendant processor(s), display units, storage units, and communications devices) of the type conventional in the art, comprises connectors 108 that provide software interfaces to legacy and other databases, data streams, and sources of information-collectively, databases 140 —in clinical care facilities or other entities (such as agency field offices or laboratories), organizations (such as a governmental agencies) or enterprises, such as the PHIN network, the HAN network or otherwise.
- a “hologram” data store 114 (hereinafter, “data store” or “hologram data store”), which is coupled to the databases 140 via the connectors 108 , stores data from those databases 140 .
- a framework server 116 accesses the data store 114 , presenting selected data to (and permitting queries from) a user browser 118 .
- the server 116 can also permit updates to data in the data store 114 and, thereby, in the databases 140 . These updates can include both the addition of new data and the modification of old data.
- databases 140 include a database 140 a maintained with a Sybase® database management system, a database 140 b maintained with an Oracle® database management system.
- the “databases” 140 also include a data stream 140 c providing information from other nodes 100 b , 100 c , 100 d , 100 e , of the PHIN, HAN, NEDSS or other network 120 .
- Those other nodes can be constructed and operated in the manner of system 100 (as suggested in the illustration by their depiction using like silhouettes) or in any other manner consistent with PHIN, HAN, NEDSS or other network operations.
- the network 120 represents the Internet, wide area network or other medium or collection of media that permit the transfer of information (continuous, periodic or otherwise) between the nodes in a manner consistent with requirements of PHIN, HAN, NEDSS or other applicable network standards.
- databases 140 provide access to information of actual or potential interest to the node in which system 100 resides and that they can be accessed via application program interfaces (API) or other mechanisms dictated by the PHIN, HAN, NEDSS or other applicable network.
- API application program interfaces
- Connectors 108 serve as interfaces to databases, streams and other information sources 140 .
- Each connector applies requests to, and receives information from, a respective database, using that database's API or other interface mechanism, e.g., as dictated by the PHIN, HAN or other otherwise.
- connector 108 a applies requests to database 140 a using the corresponding SAP API
- connector 108 b applies requests to database 140 b using the Oracle API
- connector 108 c applies requests to and/or receives information from the stream or information source 140 c use PHIN-appropriate, HAN-appropriate, NEDSS-appropriate or other stream or network-appropriate requests.
- the connector 108 c can generate requests to the network 120 to obtain data from health care institutions and other nodes on the network.
- the requests can be simple queries, such as SQL queries and the like (e.g., depending on the type of the underlying database and its API) or more complex sets of queries, such as those commonly used in data mining.
- one or more of the connectors can use decision trees, statistical techniques or other query and analysis mechanisms known in the art of data mining to extract information from the databases.
- Specific queries and analysis methodologies can be specified by the hologram data store 114 or the framework server 116 for application by the connectors.
- the connectors themselves can construct specific queries and methodologies from more general queries received from the data store 114 or server 116 .
- request-specific items can be “plugged” into query templates thereby effecting greater speed and efficiency.
- the requests can be stored in the connectors 108 for application and/or reapplication to the respective databases 108 to provide one-time or periodic data store updates.
- Connectors can use expiration date information to determine which of a plurality of similar data to return to the data store, or if dates are absent, the connectors can mark returned data as being of lower confidence levels.
- the connector 108 c (and/or other functionality not shown) provides for the automated exchange of data between public health partners, as required of nodes in the PHIN network.
- the connector 108 c (and/or other functionality) comprises an ebXML compliant SOAP web service that can be reached via an HTTPS connection after appropriate authentication and comprises, or is coupled to, an HTTPS port. It also supports messaging in the industry standard requisite formats and message content specified by the PHIN standard.
- the connector 108 c also provides for translation of messages received from the network 120 into a format compatible with the NEDSS and/or other requisite data models specified by the PHIN standards for storage in the data store 114 as detailed further below.
- connector 108 c (or other functionality) facilitates the exchange and management of specimen and lab result information, as required under the PHIN standard.
- Systems 100 according to the invention used as part of HAN or NEDSS-compatible networks provide similar functionality, as particularly required under those initiatives.
- Data and other information generated by the databases, streams and other information sources 140 in response to the requests are routed by connectors to the hologram data store 114 .
- That other information can include, for example, expiry or other adjectival data for use by the data store in caching, purging, updating and selecting data.
- the messages can be cached by the connectors 108 , though, they are preferably immediately routed to the store 114 .
- server 116 Any triples implicated by the change are created or changed in store 114 C, as are the corresponding RDF document objects in store 114 A.
- An indication of these changes can be forwarded to the respective databases, streams or other information sources 140 via the connectors 108 , which utilize the corresponding API (or other interface mechanisms) to alert those sources 140 of updates.
- changes made directly to the store 114 C e.g., using a WebDAV client or otherwise, can be forwarded by the connector 108 to the respective sources 140 .
- the hologram data store 114 stores data from the databases 140 (and from the frame-work server 116 , as discussed below) as RDF triples.
- the data store 114 can be embodied on any digital data processing system or systems that are in communications coupling (e.g., as defined above) with the connectors 108 and the framework server 116 .
- the data store 114 is embodied in a workstation or other high-end computing device with high capacity storage devices or arrays, though, this may not be required for any given implementation.
- the hologram data store 114 may be contained on an optical storage device, this is not the sense in which the term “hologram” is used. Rather, it refers to its storage of data from multiple sources (e.g., the databases 140 ) in a form which permits that data to be queried and coalesced from a variety of perspectives, depending on the needs of the user and the capabilities of the framework server 116 .
- a preferred data store 114 stores the data from the databases 140 in subject-predicate-object form, e.g., RDF triples, though those of ordinary skill in the art will appreciate that other forms may be used as well, or instead.
- RDF is a way of expressing the properties of items of data. Those items are referred to as subjects. Their properties are referred to as predicates. And, the values of those properties are referred to as objects.
- an expression of a property of an item is referred to as a triple, a convenience reflecting that the expression contains three parts: subject, predicate and object.
- RDF triples here, expressed in extensible markup language (XML) syntax.
- XML extensible markup language
- Subjects are indicated within the listing using a “rdf:about” statement.
- the second line of the listing defines a subject as a resource named “postal://zip#02886.” That subject has predicates and objects that follow the subject declaration.
- One predicate, ⁇ town> is associated with a value “Warwick”.
- Another predicate, ⁇ state> is associated with a value “RI”.
- the listing shows properties for the subject “postal://zip#02901,” namely, ⁇ town> “Providence,” ⁇ state> “RI,” ⁇ country> “US” and ⁇ zip> “02901.”
- URIs uniform resource indicators
- URI Uniform Resource Identifiers
- RRC 2396 Generic Syntax
- predicates are expressed in the form ⁇ scheme>:// ⁇ path># ⁇ fragment>, as is evident to those in ordinary skill in the art.
- the ⁇ scheme> for the predicates is “http” and ⁇ path> is “www.metatomix.com/postalCode/1.0.”
- the ⁇ fragment> portions are ⁇ town>, ⁇ state>, ⁇ country> and ⁇ zip>, respectively. It is important to note that the listing is in some ways simplistic in that each of its objects is a literal value. Commonly, an object may itself be another subject, with its own objects and predicates. In such cases, a resource can be both a subject and an object, e.g., an object to all “upstream” resources and a subject to all “downstream” resources and properties. Such “branching” allows for complex relationships to be modeled within the RDF triple frame-work.
- FIGS. 1A-1B of U.S. patent application Ser. No. 10/302,764, filed Nov. 21, 2002, entitled “Methods and Apparatus for Querying a Relational Data Store Using Schema-Less Queries” depict an architecture for a preferred hologram data store 114 according to the invention.
- the illustrated store includes a model document store and a model document manager. It also includes a relational triples store, a relational triples store manager, and a parser interconnected as shown in the drawing.
- RDF triples maintained by the store are received—from the databases (via connectors) and/or from time-based data reduction module—in the form of document objects, e.g., of the type generated from a Document Object Model (DOM) in a JAVA, C++ or other application.
- DOM Document Object Model
- the model document manager manages storage/retrieval of the document object to/from the model document store.
- the manager comprises the Slide content management and integration framework, publicly available through the Apache Software Foundation. It stores (and retrieves) document objects to (and from) the store in accord with the WebDAV protocol.
- WebDAV protocol a protocol for storing document objects to (and from) the store.
- WebDAV protocol allows for adding, updating and deleting RDF document objects using a variety of WebDAV client tools (e.g., Microsoft Windows Explorer, Microsoft Office, XML Spy or other such tools available from a variety of vendors), in addition to adding, updating and deleting document objects via connectors and/or time-based data reduction module.
- WebDAV client tools e.g., Microsoft Windows Explorer, Microsoft Office, XML Spy or other such tools available from a variety of vendors
- This also allows for presenting the user with a view of a traversable file system, with RDF documents that can be opened directly in XML editing tools or from Java programs supporting WebDAV protocols, or from processes on remote machines via any HTTP protocol on which WebDAV is based.
- RDF triples received by the store are also stored to a relational database that is managed and accessed by a conventional relational database management system (RDBMS), operating in accord with the teachings hereof.
- RDBMS relational database management system
- the triples are divided into their constituent components (subject, predicate, and object), which are indexed and stored to respective tables in the manner of a “hashed with origin” approach.
- a parser extracts its triples and conveys them to the RDBMS with a corresponding indicator that they are to be added, updated or deleted from the relational data-base.
- Such a parser operates in the conventional manner known in the art for extracting triples from RDF documents.
- the database store has five tables interrelated as shown in the aforementioned incorporated figures. In general, these tables rely on indexes generated by hashing the triples' respective subjects, predicates and objects using a 64-bit hashing algorithm based on cyclical redundancy codes (CRCs)—though, it will be appreciated that the indexes can be generated by other techniques as well, industry-standard, proprietary or otherwise.
- CRCs cyclical redundancy codes
- the “triples” table maintains one record for each stored triple.
- Each record contains an aforementioned hash code for each of the subject, predicate and object that make up the respective triple, along with a resource flag (“resource_flg”) indicating whether that object is of the resource or literal type.
- resource_flg a resource flag
- Each record also includes an aforementioned hash code (“m_hash”) identifying the document object (stored in model document store) from which the triple was parsed, e.g., by the parser.
- the values of the subjects, predicates and objects are not stored in the triples table. Rather, those values are stored in the resources table, namespaces table and literals table.
- the resources table in conjunction with the namespaces table, stores the subjects, predicates and resource-type objects; whereas, the literals table stores the literal-type objects.
- the resources table maintains one record for each unique subject, predicate or resource-type object.
- Each record contains the value of the resource, along with its aforementioned 64-bit hash. It is the latter on which the table is indexed.
- portions of those values common to multiple resources e.g., common ⁇ scheme>:// ⁇ path> identifiers
- r_value contained in each record of the resources table reflects only the unique portion (e.g., ⁇ fragment> identifier) of each resource.
- the namespaces table maintains one record for each unique common portion referred to in the prior paragraph (hereinafter, “namespace”). Each record contains the value of that namespace, along with its aforementioned 64-bit hash. As above, it is the latter on which this table is indexed.
- the literals table maintains one record for each unique literal-type object. Each record contains the value of the object, along with its aforementioned 64-bit hash. Each record also includes an indicator of the type of that literal (e.g., integer, string, and so forth). Again, it is the latter on which this table is indexed.
- the models table maintains one record for each RDF document object contained in the model document store.
- Each record contains the URI of the corresponding document object (“uri_string”), along with its aforementioned 64-bit hash (“m_hash”). It is the latter on which this table is indexed.
- uri_string the URI of the corresponding document object
- m_hash 64-bit hash
- the relational triples store is a schema-less structure for storing RDF triples.
- triples maintained in that store can be reconstituted via an SQL query. For example, to reconstitute the RDF triple having a subject equal to “postal://zip#02886”, a predicate equal to “http://www.metatomix. com/postalCode/1.0#town”, and an object equal to “Warwick”, the following SQL statement is applied:
- RDF documents and, more generally, objects maintained in the store can be contained in other stores—structured relationally, hierarchically or otherwise—as well, in addition to or instead of the stores illustrated in the aformentined incorporated figures.
- the maintenance of data in the store 114 is accomplished in a manner compatible with the applicable PHIN standards, e.g., for the use of electronic clinical data for event detection.
- data storage is compatible with the applicable logical data model(s), can associate incoming data with appropriate existing data (e.g., a report of a disease in a person who had another condition previously reported), permits potential cases should be “linked” and traceable from detection via electronic sources of clinical data or manual entry of potential case data through confirmation via laboratory result reporting, and permits data to be accessed for reporting, statistical analysis, geographic mapping and automated outbreak detection algorithms, and so forth, all as required under the PHIN standards and further discussed below.
- a system 100 according to the invention used as part of the PHIN network provides directories of public health and clinical personnel accessible as required under the PHIN standards.
- Systems 100 according to the invention used as part of HAN or NEDSS-compatible networks provide similar functionality, as particularly required under those initiatives.
- the relational triples store manager discussed above supports SQL queries such as the one exemplified above (for extracting a triple with the subject “postal://zip#02886”, the predicate “http://www.metatomix.com/postalCode/1.0#town”, and the object “Warwick”), in the manner described in commonly assigned U.S. patent application Ser. No. 10/302,764, filed Nov. 21, 2002, entitled METHODS AND APPARATUS FOR QUERYING A RELATIONAL DATA STORE USING SCHEMA-LESS QUERIES, the teachings of which are incorporated herein by reference (see, specifically, for example, FIG. 3 thereof and the accompanying text).
- the data store can likewise include time-wise data reduction component of the type described in commonly assigned U.S. patent application Ser. No. 10/302,727, filed Nov. 21, 2002, entitled METHODS AND APPARATUS FOR STATISTICAL DATA ANALYSIS AND REDUCTION FOR AN ENTERPRISE APPLICATION, the teachings of which are incorporated herein by reference (see, specifically, for example, FIG. 3 thereof and the accompanying text), to perform a time-wise reduction on data from the database, streams or other sources.
- data store 114 includes a graph generator that uses RDF triples to generate directed graphs in response to queries made—e.g., by a user accessing the store via the browser 118 and server 116 , by a surveillance, monitoring and real-time events application executing on the server 116 or in connection with the browser 118 , by another node on the network 120 and received electronically or otherwise, or made otherwise—for information reflected by triples originating from data in one or more of the databases, streams or other sources 140 .
- queries made e.g., by a user accessing the store via the browser 118 and server 116 , by a surveillance, monitoring and real-time events application executing on the server 116 or in connection with the browser 118 , by another node on the network 120 and received electronically or otherwise, or made otherwise—for information reflected by triples originating from data in one or more of the databases, streams or other sources 140 .
- Such generation of directed graphs from triples can be accomplished in any conventional manner known the art (e.g., as appropriate to RDF triples or other manner in which the information is stored) or, preferably, in the manner described in co-pending, commonly assigned U.S. patent application Ser. No. 10/138,725, filed May 3, 2002, entitled METHODS AND APPARATUS FOR VISUALIZING RELATIONSHIPS AMONG TRIPLES OF RESOURCE DESCRIPTION FRAMEWORK (RDF) DATA SETS (corresponding to PCT Application WO03094142, published Nov. 13, 2003), and Ser. No. 60/416,616, filed Oct.
- Directed graphs so generated can be passed back to the server 116 for presentation to the user via browser 118 , they can be “walked” by the server 116 to identify specific information responsive to queries, or otherwise.
- the data store 114 can utilize genetic, self-adapting, algorithms to traverse the RDF triples in response to such queries.
- the data store utilizes a genetic algorithm that performs several searches, each utilizing a different methodology but all based on the underlying query from the framework server, against the RDF triples. It compares the results of the searches quantitatively to discern which produce(s) the best results and reapplies that search with additional terms or further granularity.
- surveillance, monitoring and real-time events applications executing on the connectors 108 , the server 116 , the browser and/or the data store 114 utilize an expert engine-based system to identify information in the data store 114 and/or from sources 140 responsive to queries and/or otherwise for presentation via browser 118 , e.g., in the form of alerts, reports, or otherwise.
- the information so identified can, instead or in addition, form the basis of further processing, e.g., by such surveillance, monitoring and real-time events applications, in the form of broadcasts or messages to other nodes in the network 120 , or otherwise, consistent with requirements of PHIN, HAN or other applicable standards.
- the expert engine-based system can be used to process data incoming from the sources 140 to determine whether it should be ignored, stored, logged for alert or classified otherwise.
- Data reaching a certain classification limit can be displayed via the browser 118 and, more particularly, the dashboard discussed below, e.g., along with a map of the state, country or other relevant geographic region and/or along with other similar data.
- the expert engine-based system can be used to detect the numbers of instances occurring over time and, if the number exceeds a threshold, to generate a report, e.g., for display via a dashboard window, or generate alert messages for transfer over the network 120 to targeted personnel (e.g., as identified by action of further rules or otherwise).
- the expert engine can also be used to subset data used for display or reporting in connection with the collaborative function, e.g., specified under the CDC's HAN guidelines.
- the system 2008 includes a module 2012 that executes a set of rules 2018 with respect to a set of facts 2016 representing criteria in order to (i) generate a subset 2020 of a set of facts 2010 representing an input data set, (ii) trigger a further rule, and/or (iii) generate an alert, broadcast, message, or otherwise.
- a module 2012 executes a set of rules 2018 with respect to a set of facts 2016 representing criteria in order to (i) generate a subset 2020 of a set of facts 2010 representing an input data set, (ii) trigger a further rule, and/or (iii) generate an alert, broadcast, message, or otherwise.
- the set of facts 2016 representing criteria are referred to as “criteria” or “criteria 16 ,” while the set of facts 2010 representing data are referred to as “data” or “data 2010 .”
- Illustrated module 2012 is an executable program (compiled, interpreted or otherwise) embodying the rules 2018 and operating in the manner described herein for identifying subsets of directed graphs.
- module 2012 is implemented in Jess (Java Expert System Shell), a rule-based expert system shell, commercially available from Sandia National Laboratories. However it can be implemented using any other “expert system” engine, if-then-else network, or other software, firmware and/or hardware environment (whether or not expert system-based) suitable for adaptation in accord with the teachings hereof.
- the module 2012 embodies the rules 2018 in a network representation 2014 , e.g., an if-then-else network, or the like, native to the Jess environment.
- the network nodes are preferably executed so as to effect substantially parallel operation of the rules 2018 , though they can be executed so as to effect serial and/or iterative operation as well or in addition.
- the rules are represented in accord with the specifics of the corresponding engine, if-then-else network, or other software, firmware and/or hardware environment on which the embodiment is implemented. These likewise preferably effect parallel execution of the rules 18 , though they may effect serial or iterative execution instead or in addition.
- the data set 2010 can comprise any directed graph, e.g., a collection of nodes representing data and directed arcs connecting nodes to one another, though in the illustrated embodiment it comprises RDF triples contained in the data store and/or generated from information received from the other sources via connectors.
- the data set can comprise data structures representing a meta directed graph of the type disclosed in co-pending, commonly assigned U.S. patent application Ser. No. 10/138,725, filed May 3, 2002, entitled METHODS AND APPARATUS FOR VISUALIZING RELATIONSHIPS AMONG TRIPLES OF RESOURCE DESCRIPTION FRAMEWORK (RDF) DATA SETS, e.g., at FIG. 4A-6B and accompanying text, all of which incorporated herein by reference.
- RDF RESOURCE DESCRIPTION FRAMEWORK
- Criteria 2016 contains expressions including, for example, literals, wildcards, Boolean operators and so forth, against which nodes in the data set are tested.
- the criteria can specify subject, predicate and/or object values or other attributes.
- the criteria can be input by a user, e.g., via a browser, e.g., on an ad hoc basis. Alternatively or in addition, they can be generated by surveillance, monitoring and real-time events applications executing on the connectors, the server, the browser and/or the data store.
- Rules 2018 define the tests for identifying data in the data set 2020 that match the criteria or, where applicable, are related thereto. These are expressed in terms of the types and values of the data items as well as their interrelationships or connectedness.
- a set of rules applicable to a data set comprised of RDF triples for identifying triples that match or are related to the criteria are disclosed in aforementioned incorporated by reference U.S. Patent Application Ser. No. 60/416,616, filed Oct. 7, 2002, entitled METHODS AND APPARATUS FOR IDENTIFYING RELATED NODES IN A DIRECTED GRAPH HAVING NAMED ARCS.
- the data 2020 output or otherwise generated by module 2012 represents those triples matching (or, where applicable, related) to the criteria as determined by exercise of the rules.
- the data 2020 can be output as triples or some alternate form, e.g., pointers or other references to identified data within the data set 2010 , depending on the needs of the surveillance, monitoring and real-time events application that invoked the system 2008 .
- the module 2012 instead of or in addition to outputting data 2020 , the module 2012 triggers execution of further rules, generate alerts, broadcasts, messages, or otherwise, consistent with requirements of PHIN, HAN or other applicable standards.
- triples identified by the expert engine-based system can be output as such or in alternate form, e.g., pointers or other references to identified data within the data set 10 , depending on the needs of the surveillance, monitoring and real-time events application that invoked the system 8 .
- the identified triples can trigger execution of further rules (e.g., in the expert engine system), generate alerts, broadcasts, messages, or otherwise, consistent with requirements of PHIN, HAN or other applicable standards.
- the framework server 116 presents information from the data store 114 and/or sources 140 via browser 118 . This can be based on requests entered directly by the user directly, e.g., in response to selections/responses to questions, dialog boxes or other user-input controls generated by a surveillance, monitoring and real-time events application executing on the server 116 or in connection with the browser 118 . It can also be based, for example, on information obtained from the database 114 and/or sources 140 by the expert engine-based system 8 described above.
- system 100 may provide a surveillance, monitoring and real-time events application that includes a “dashboard” with display windows or panels that provide comprehensive real-time displays of information gathered from the data store 114 or other sources 140 , as well as “alerts” resulting from anomalous situations detected by the surveillance, monitoring and real-time events application.
- the dashboard and alerts can be generated by an application executing on the server 116 and/or the browser 118 or otherwise.
- monitoring and real-time events dashboards can display information and alerts that are specific to predefined categories, such as boarder and port security, health and bioterrorism, or public and community safety. These can be configured by users to display information from ad hoc combinations of data sources and user-defined alerts.
- predefined categories such as boarder and port security, health and bioterrorism, or public and community safety.
- FIG. 7 illustrates a border/port security dashboard 400 .
- the dashboard displays several panels 402 , 404 , 406 , 408 , 410 , 412 and 414 .
- Panel 402 can be used to display information relating to an alert, if one has been issued by the surveillance, monitoring and real-time events application or by an external system. Panel 402 is described in more detail below.
- Each panel 404 - 414 displays information from a particular data source or an aggregation of data from several data sources.
- panel 404 can contain real-time radar data from the US Coast Guard superimposed on a satellite image of Boston's inner harbor.
- the panel 404 display can be augmented with other Coast Guard data.
- GPS global positioning system
- US Coast Guard vessels and vehicles can be used to identify and then look up information related to these units.
- the unit identities can be superimposed on the image displayed in panel 404 , as shown at 416 , 418 and 420 . Double-clicking on one of these units can cause the surveillance, monitoring and real-time events application to display information about the unit.
- This information can include, for example, contact information (e.g. frequency, call sign, name of person in charge, etc.), capabilities (e.g. maximum speed, crew size, weaponry, fire-fighting equipment, etc.) and status (e.g. docked, patrolling, busy intercepting a vessel, etc.).
- Panel 406 can contain real-time data from a port authority superimposed on a map of the inner harbor.
- port authority data can include information related to the inner harbor that is different than information provided by the US Coast Guard.
- the port authority data can include information on vessels traveling or docked within the inner harbor.
- the port authority data can relate to more than just the inner harbor.
- the port authority data can include information related to an airport and a rail yard.
- Panel 410 and 412 can display information from other data sources, such as US Customs and local or state police.
- Panel 408 displays a current Homeland Security Advisory System threat level.
- Panel 414 displays contact information for agencies, such as the US Coast Guard, US Customs, port authority and state police, that might be invoked in case of an alert.
- a user can double-click on any panel to display a separate window containing the panel. By this mechanism, the user can enlarge any panel.
- the user can zoom in on a portion of the image displayed by a panel. For example, the user can select a point on the panel display to re-center the display to the selected point and zoom in on that point.
- the user can select a rectangular portion of the panel display using a “rubber band” cursor and instruct the system to fill the entire panel with the selected portion.
- FIG. 8 illustrates an example of such a window 500 displaying the port authority panel 406 of FIG. 7 .
- a user can, for example, double-click on a vessel 502 to display information about the vessel.
- FIG. 9 illustrates an example of a pop-up window 600 that displays information about the selected vessel.
- panels 402 - 414 contain graphical displays
- other panels can contain textural or numeric data.
- panels containing shipping schedules, airline schedules, port volume statistics, recent headlines, weather forecasts, etc. can be available for display.
- other graphical panels such as current meteorological data for various portions of the world, can also be available.
- the surveillance, monitoring and real-time events application can make available more panels than can be displayed at one time on the dashboard 400 ( FIG. 7 ).
- the dashboard 400 can display a default set of panels, such as panels 404 - 414 .
- the user can select which panels to display in the dashboard 400 , as well as arrange the panels within the dashboard and control the size of each panel. If it is deemed desirable to display more panels than can be displayed at one time, some or all of the desired panels can be displayed on a round-robin basis.
- the surveillance, monitoring and real-time events application can include rules and/or heuristics to automatically detect anomalies and alert users to these anomalies (hereinafter referred to as “alerts”).
- alerts the surveillance, monitoring and real-time events application preferably can select one or more panels containing particularly relevant information and display or enlarge those panels. The selected panels need not be ones that the user could select.
- the surveillance, monitoring and real-time events application can create a new panel that includes a combination of data from several sources, the sources being selected by rule(s) that caused the alert to be issued.
- the surveillance, monitoring and real-time events application can include rules describing permitted, required and/or prohibited behavior of vessels in these shipping lanes 700 and 702 .
- Some rules can apply to all vessels.
- Other rules can apply to only certain vessels, for example according to the vessels' types, cargos, speeds, country of registry, as well as according to data unrelated to the vessels, such as time of day, day of week, season, Homeland Security Advisory System threat level, amount of other harbor traffic or amount or schedule of non-harbor traffic, such as aircraft at an adjacent airport.
- Other rules can apply to docked vessels, vessels under tow, etc.
- rules can apply to aircraft, vehicles, or any measurable quantity, such as air quality in a subway station, seismic data, voltage in a portion of a power grid or vibration in a building, bridge or other structure. Rules can also apply to data entered by humans, such as the number of reported cases of food poisoning or quantities of antibiotics prescribed, ordered or on hand during a selected period of time.
- the dashboard 400 displays a default set of panels or a set of panels selected by the user, as previously described. If, for example, the previously mentioned tanker vessel 502 ( FIG. 10 ) carrying a hazardous cargo, such as liquefied natural gas (LNG), deviates 704 from a prescribed course, the surveillance, monitoring and real-time events application can issue an alert. Note that rules for vessels carrying hazardous cargos can be different than for vessels carrying non-hazardous cargos. In addition, other vessels can trigger the alert. For example, if the LNG tanker 502 is traveling within its prescribed course, but a high-speed vessel (not shown) or an aircraft is on a collision course with the LNG tanker, the surveillance, monitoring and real-time events application can issue an alert.
- a hazardous cargo such as liquefied natural gas (LNG)
- LNG liquefied natural gas
- other vessels can trigger the alert. For example, if the LNG tanker 502 is traveling within its prescribed course, but a high-speed vessel (not shown) or an aircraft is on a
- the surveillance, monitoring and real-time events application displays the alert panel 402 ( FIG. 7 ) and an alert message 422 .
- the alert panel 402 displays a zoomed-in portion of the port authority panel 406 .
- the surveillance, monitoring and real-time events application can automatically notify a predetermined list of people or agencies. The particular people or agencies can depend on factors, such as the time of day or the day of the week of the alert.
- the surveillance, monitoring and real-time events application can notify other users at other nodes, such as nodes 100 b , 100 c , 100 d and/or 100 e ( FIG. 5 ).
- Information displayed on dashboards (not shown) at these other nodes 100 b - e need not be the same as information displayed on the dashboard 400 .
- the information displayed on these other nodes 100 b - e can be more or less detailed than the information displayed on the dashboard 400 .
- summary information such as an icon displayed on a map of the United States, can be displayed at command/control node to indicate an alert in Boston, without necessarily displaying all details related to the alert.
- a user at the command/control node can double-click on the icon to obtain more detailed information.
- FIGS. 11-19 illustrate an exemplary dashboard that can be used in a health and bioterrorism context.
- FIG. 11 illustrates a dashboard 800 that contains several panels 802 , 804 , 806 , 808 and 810 .
- Panel 802 contains a map of the U.S. with icons 812 , 814 , 816 indicating locations of three alerts.
- Panel 804 contains emergency contact information that is relevant to the alerts.
- Panel 806 contains hyperlinks to discussion forums, in which agency representatives and other authorized groups and people can post messages and replies, as is well known in the art.
- Panel 808 contains hyperlinks to information that is relevant to the alerts.
- Panel 810 displays the current Homeland Security Advisory System threat level. These panels will be described in more detail below.
- the icons 812 , 814 and 816 represent medical care providers that have experienced noteworthy events or levels of activity.
- an alert can be issued if, for example, the number of cases of disease, such as influenza, exceeds a predetermined threshold.
- Provider 3 has encountered patients with pneumonia that does not respond to antibiotics.
- the other alerts could relate to other anomalous events or levels of activity.
- Clicking the icon 816 causes the system to display information 818 related to the selected alert.
- Clicking on a link 820 causes the system to display more detailed information about the alert.
- FIG. 12 illustrates two panels 902 and 904 , as well as a user selection area 906 , that can be displayed.
- Panel 902 contains a more detailed map of the area in which the event occurred.
- Panel 904 list the number of cases by zip code of the patients.
- User selection area 906 enables the user to select one or more of the alerts, thereby selecting or aggregating data from the selected provider(s) for display in panels 902 and 904 .
- panel 804 contains icons for government agencies and other individuals or organizations (collectively “responders”) that might be called upon to respond to manage a biological, nuclear, foodborne or other situations identified by the expert engine-based system 8 (e.g., as where the number of instances matching a specified critereon exceeds a threshold).
- Clicking link 822 displays a window containing emergency contact information for these responders, as shown in FIG. 13 at 1000 .
- Panel 1002 contains several emergency callout options, by which the user can manage the alerts. For example, clicking “Message Board” link 1004 displays a window containing messages posted in relation to this alert, as shown in FIG. 14 at 1100 . This message board enables users and responders to communicate with each other in relation to the alert.
- An “Initiate a new Callout” link 1102 enables the user to initiate a new situation, as shown in FIG. 15 .
- the surveillance, monitoring and real-time events application In response to an alert, the surveillance, monitoring and real-time events application automatically performs searches of the Internet and responder intranets for information relevant to the alert.
- panel 808 FIG. 11
- the surveillance, monitoring and real-time events application can, for example, have a database of information sources catalogued according to alert type. As shown in FIG. 16 , clicking on one of the hyperlinks in the panel 808 opens a new window 1300 displaying contents identified by the hyperlink.
- the user can select a module via a pull-down list 824 .
- the user can select “Reports”, in which case the system displays a window similar to that shown in FIG. 17 .
- the system displays a report in a report panel 1406 .
- FIG. 18 illustrates another graphical display 1500 , by which the system can display an alert.
- the system displays information, such as proximity of the outbreak to the nearest residential area, as well as the population of the residential area, proximity to the nearest emergency medical center and the number of free beds in the medical center.
- the surveillance, monitoring and real-time events application can query those hospital systems and display relevant information, as shown in FIG. 19 .
- FIG. 6 depicts a surveillance, monitoring and real-time events system 100 as described above in which one or more functions of the digital data processing application resident at the respective node are carried out by computer 200 —here, depicted having the form-factor of a server or application “appliance” (but optionally having other form factors in other embodiments).
- the functions subsumed by appliance 200 are those of data store 114 and server 116 , though in other embodiments it may have other functions in addition or instead.
- appliance 200 is configured to provide automatic integration and correlation functions, among others, thereby facilitating its installation and use at a node. In other embodiments, other functions may be configured for automatic operation, in addition or instead.
- illustrated appliance includes display 202 configured to display output of the above-mentioned dashboard application. Such display 202 is optional, however, and may not be provided in other embodiments.
- illustrated appliance 200 provides for automatic or semiautomatic recognition (e.g., of networks, other nodes, data sources, and so forth), automatic or semi-automatic configuration (e.g., with respect to other computers and equipment in the same node, data sources, other nodes, and so forth), drag-and-drop, double-click or other user-responsive administration, and process automation.
- illustrated appliance 200 provides for automatic or semi-automatic ontology, framework selection (OFS), e.g., with respect to PHIN, HAN, NEDSS or other public health & bioterrorism applications, border & port security applications, public & community safety applications, and government data integration applications, among others, automatic data source ontology selection, and drag-and-drop ontology mapping.
- Additional automatic or semi-automatic functions provided by the appliance 200 include natural language rules administration, real-time reporting, and inferencing.
- appliance 200 may provide other functions automatically or semi-automatically, in addition or instead of those listed above.
- appliance 200 as used on one embodiment of the invention is provided in the sections that follow.
- appliance 200 is an intelligent, scalable, dynamically configurable integration appliance provided to customers in a ready-to-use format. It can be quickly and easily set up, turned on, configured, and used, saving time and labor, and money.
- 12 B is a server-based, fully functioning information integration platform, with unprecedented capabilities.
- illustrated appliance 200 is ideally suited to users who demand quick, easy, scalable, even portable information integration solutions for a variety of needs.
- These include public sector applications, such as political conventions, military applications, temporary professional sporting event venues, natural disasters, storm tracking , many more high visibility, security-intensive events; commercial sector applications, such as small company information integration, financial institution mergers for rapid integration and insights, “know your customer” initiatives for smaller financial institutions, information integration for individual travel agents, tour companies, and so forth.
- appliance 200 handles any type of data, for example wide variety of chemical, radiological, and other sensor data, government alerts including homeland security status, amber alerts, etc., meteorological information, traffic and transit information, real-time audio/video feeds and still imagery, ground-penetrating and surface radar, aerial imagery from reconnaissance flights and satellites, passive or tripwire sensor readings, GIS maps, hospital resource data: beds, staffing, equipment, medical condition and treatment information, epidemiological/syndromic surveillance data, customer spending and preferences, and financial account information, again, among others.
- data for example wide variety of chemical, radiological, and other sensor data, government alerts including homeland security status, amber alerts, etc., meteorological information, traffic and transit information, real-time audio/video feeds and still imagery, ground-penetrating and surface radar, aerial imagery from reconnaissance flights and satellites, passive or tripwire sensor readings, GIS maps, hospital resource data: beds, staffing, equipment, medical condition and treatment information, epidemiological/syndromic surveillance data, customer spending and preferences, and financial account
- Illustrated appliance 200 facilitates quick and easy connections to any data source, integrates the data sources, and provides the ability to interact with all of the information, in real-time. It provides interoperability and decision-making capabilities to the user quickly, dynamically, and efficiently. Appliance 200 can handle additional data sources on-the-fly, reflecting that information in the dashboard. There is no need for costly customization to data connections and dashboards—this powerful system handles all of that. It even integrates an expert system to automate critical alerts and notifications when certain conditions exist, based on pre-set rules.
- Appliance 200 creates knowledge and provides an unprecedented level of awareness and response by synthesizing information that could not previously be organized, processed, or acted upon.
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Abstract
Description
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- Data Stovepipes—Aggregating data from the various stovepipes is often virtually impossible. Gartner, Inc. estimates that 70 percent of corporate data resources are hosted on various mainframe systems. Butler Group found that 80 percent of corporate data is in non-relational data sources, while IDC's research shows that 40 percent of all application development effort is devoted simply to accessing existing data. What's more, Gartner also found that for every dollar spent on e-commerce implementation, somewhere between $5-$20 must be spent developing necessary integration systems.
- Conflicting Standards—It has been said many times, the great thing about IT standards is that there are so many to choose from. But those standards often compete and are a significant barrier to integrating applications and data. Whether it's Linux vs. Windows 2000, Oracle vs. SQL Server, PeopleSoft vs. SAP, or structured vs. unstructured data, enterprises must support a wide variety of incompatible standards and protocols, representing a substantial hidden cost to the enterprise.
- Real-Time Visibility—Even if you get the data out from its sources in a usable format, it's often too late to be of value. Enterprises want real-time visibility into their information.
- Disruptive Changes—Given the critical nature of most of these systems, corporate IT is loathe to introduce any changes that could trigger business-halting system instabilities.
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- Processing Power—Moore's law that establishes processor power and number of transistors doubles every 18 months continues to be proven true. We've gone from CPUs with 1,000 transistors to CPUs with 100 million transistors in a little more than 30 years—all while prices (in absolute and relative terms) have continued to decline dramatically. Memory speeds, capacities, and associated prices have seen similar adoption curves. Further, the miniaturization of these components has spawned unprecedented innovation in device sizes, form factors, and usage—as well as a surfeit of spare CPU cycles that are often untapped and idle.
- Bandwidth—The cost-curve for network bandwidth continues to drop into a deep trough. Massive infrastructure investments during the “Internet boom” and by telecomm companies in the past several years have created an unprecedented glut in capacity, driving costs down significantly. Analysts believe that as little as 8 percent of deployed fiber optic lines are “lit” and that only two percent of that capacity is being utilized. The result: historically low prices.
- Storage—In the storage sector, the adoption and cost curves are similar to those described by Moore's Law for microprocessors. Whether its disk- or chip-based persistent memory, storage capacities continue to climb while costs and form factors continue to shrink. Recently, manufacturers began showing prototypes of a hard-disk drive the size of a coin that can store 3 GB of data.
- The “Next-Generation World Wide Web”—In only a few years, the Web has witnessed a remarkable evolution from a simple communications forum for scientists and academics to a rich source of information and research to an interactive platform supporting e-commerce and other transactions. Today, Web applications have grown from simple static publishing to dynamic pages, transactional commerce sites and now, with the Semantic Web, interoperable, interconnected platforms upon which software and application providers are developing entirely new generations of innovative products and services—and standards-based systems will drive their interoperability. Open standards and protocols, open-source software, Service-Oriented Architectures (SOA), (including Web Services), and the Semantic Web, that uses the Resource Description Framework (RDF) to bring together disparate data sources, drive this.
- Service-Oriented Architectures—The sharing of modularized components (“services”) using standard interfaces has had a dramatic impact on enterprise applications. SOAs such as Web Services have helped simplify point-to-point integration. However, this use of Web Services only scratches the surface of its deeper potential to enable companies to assemble dynamic, agile business processes and IT systems that can respond easily to change. Analysts believe that SOA will be the dominant approach to distributed computing by 2006 and that 69 percent of the enterprise software market will be service-oriented by 2010, representing an overall market of $98 billion.
- Grid Computing—Another major developing trend lies in the area of on-demand grid computing. Like the familiar electrical grid we rely on for near-ubiquitous electrical service, grid computing assembles all of an enterprise's available networked resources from servers down to desktop computers into a single, seamless, virtual resource of processing, network bandwidth, and storage capacity, and data library that is available to users on demand.
- Computational Grid—When viewing grids as a collection of connected machines, they all contribute a combination of resources to the grid. The most common resource contributed to the traditional grid is that of computing cycles (or CPU horsepower). These resources are used to:
- Run CPU-intensive applications across a grid, rather than on a single (or single set) of machines.
- Run applications modules (assuming the application is designed to divide its work)
- Run applications that need to run many times off different machines on the grid
- Storage Grid (Storage Network Management)—In the case of storage grids, the machines on the grid provides some transparent and scalable quantity of storage for grid use. (It is safe to assume that some resources on a grid contribute to both computational grids as well as storage grids). The concept of storage is not limited to long-term storage (non-volatile storage), but also to cache storage available within any given machine or resource. Storage Grids provide the foundation for information-based grid computing found in data grids.
- Data Grid—Data grids provide for applications to use data from anywhere (assuming the appropriate security permissions). A federated approach to data grids enables users to maintain full control of their own data and information systems while contributing data to data grid-based applications. One can view this as distributed data access. As realized by the inventors hereof, the largely unaddressed challenge here lies in creating the ability to not only access data from disparate and geographically distributed data systems, but to create information from that data in a single-unified view. And, as evident in the discussion below, grid computing applications in accord with the invention take on the requirements of EII in support of comprehensive information integration, aggregation and interaction.
-
- Real-Time Grid Management
- Enterprise Asset Management
- Command/Control/Communication Services to run applications
- Policy-Based Decision Making
- Integration With Provisioning Tools
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- Data Aggregation—apparatus, platforms and methods according to the invention use a non-invasive, Internet-based messaging-oriented infrastructure (using SOAP, WADL, UDDI, etc.) to quickly extract data from disparate sources (such as contemporary CRM, SFA applications and data warehouses, as well as legacy systems and data files), transform it into Resource Description Framework (RDF, an advanced for of XML), and create and automatically apply your customized business rules. This scalable, fault-tolerant solution requires only simple database connections—and no changes to existing gray matter applications or databases. It also conforms to the existing security and integrity of your existing information architecture. With apparatus, platforms and methods according to the invention, you can use and reuse high-level abstract components to quickly assemble and modify a large number of distributed “processing chains” that interconnect your gray matter applications.
- Information Integration—The ability to integrate disparate into meaningful information models provides the new class of white matter applications that provide enterprise knowledge through monitoring, analysis, and decision support. Apparatus, platforms and methods according to the invention leverage the Semantic Web in its own real-time, data cache—a platform-independent metadata repository that enables you to bring data together and analyze it for previously unseen patterns, commonalities, and relationships. Apparatus, platforms and methods according to the invention provides a persistent store of information objects where the data expressed is abstract from the way it is stored, enabling structured and unstructured data alike to be collected and combined.
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- Real-Time Interaction—apparatus, platforms and methods according to the invention deliver dynamic, real-time, interactive “composite applications” that monitor and report on real-time data from disparate sources. The customizable business-insight dashboard provides the single view of real-time information and a level of two-way interactivity never before possible.
-
- Improved Resource Utilization—Studies show that the average corporate server uses only 20 percent of its full capacity. Apparatus, platforms and methods according to the invention enable IT departments to harness and marshal their resources to optimally manage a unified, seamless computing resource.
- Next-Generation XML Metadata-Driven Design—Apparatus, platforms and methods according to the invention eliminate the constraints of traditional relational-based data modeling, the dynamic, simple-schema data model offers the first and best commercial implementation of the W3C's standard Resource Description Framework (RDF) standard.
- BPA Rules Engine—Apparatus, platforms and methods according to the invention automate your responses and decisions—and acts on complex situations without the overhead of code embedded in multiple gray matter applications. Apparatus, platforms and methods according to the invention reduce implementation and management costs through a powerful inference engine that eliminates the need to code for fact/rule interpretations.
- Flexibility—You can dynamically add or delete data sources, query the platform's data cache, or deploy in a distributed architecture.
- Unprecedented Openness—With apparatus, platforms and methods according to the invention, you're not tied to any vendor's DBMS, file system, application, operating system, or other protocol or standard. XML metadata gives you a very low-cost data provisioning, access, and integration.
- Scalability—Apparatus, platforms and methods according to the invention offers scalability proven in numerous deployments. As your future needs dictate, you can deploy additional solutions based on apparatus, platforms and methods according to the invention, at minimal incremental cost.
- Low-Impact Implementation—Apparatus, platforms and methods according to the invention are a non-invasive solution that requires no changes to your databases or applications. Security within your architecture remains intact. And you can deploy multiple configurations customized to meet varying security and infrastructure needs.
- Rapid Deployment—Apparatus, platforms and methods according to the invention deliver actionable insights very quickly.
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- Achieve Real-Time Visibility Across The Enterprise—Apparatus, platforms and methods according to the invention help business analysts and managers find commonalities, trends, and patterns in aggregated data to provide new insights in ways that have never before been possible—all in real-time as dictated by the business's unique needs.
- Breakthrough Services—Apparatus, platforms and methods according to the invention enable a new-breed white matter applications that differentiate your enterprise in the eyes of customers. Collectively, these bring in new customers, improve service, keep you ahead of competitors, decrease customer churn, and increase revenue-per-customer.
- Get 360-Degree Views—Achieve the unprecedented unified view of your customer that reflects all touchpoints and interactions, regardless of customer, product, service, location, or channel. That helps you deliver new services and educate customers on how to get the most out of their relationship with your enterprise.
- Leverage an Enterprise Metadata Repository—Get a unified view of your critical enterprise information sources and their data fields. This gives you single-query access to information sources across your enterprise—a key requirement as the importance of interoperability increases.
- Meet Regulatory Standards—Initiatives such as Sarbanes-Oxley, Basel-II, Straight-Through Processing (STP), and the USA PATRIOT Act, Gamm-Leach-Bliley, HIPAA, and others are inherently data-driven challenges. Apparatus, platforms and methods according to the invention help you see, report, and act upon all the data—in real time.
- Respond With Bi-Directional Connectivity—You need more than reporting and analysis—they need to take action. Unlike warehousing or business-intelligence disciplines, apparatus, platforms and methods according to the invention support two-way communication, enabling transactional updates that write back to every data source.
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- Delivers a dual purpose real-time syndromic surveillance system covering both bioterrorism and targeted communicable diseases
- Transforms data from a variety of protocols (CSV, EDI, Excel, XML) into industry standard formats HL7 and HIPPA
- Integrates disparate data systems (hospitals, labs, clinics, pharmacies) from any format or location quickly and without custom coding
- Enables synchronous and asynchronous collaboration between participating departments and personnel
- Provides real-time customizable reporting and GIS mapping via web-based graphical interface
- Initiates and manages real-time notifications to first responders and public health officials via web, email, phone, wireless PDA and mobile phone
- Complies with the CDC's NEDSS, HAN and PHIN architectures
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- Real-time information in a secure web-based user interface
- Providing a consolidated view of port security status by integrating multiple agencies and organizations existing information systems to appear as one, in real-time.
- Integration of meteorological or other environmental information
- GIS (geo-spatial mapping) for rapid local assessment and visibility
- Time-critical risk assessment based on local, state and federal data sources
- Scenario-based event management for medical, emergency and public safety responders with immediate notifications to key safety personnel
-
- Real-time reporting with secure web-based user interface enabling a single view of a multi-agency operation
- Integration of critical data from existing data sources (any data in any format) to create better public safety information
- GIS (geo-spatial mapping) for rapid local assessment and visibility
- Real-time risk assessment based on local, state and federal data sources
- Coordinated communication and immediate notifications to key safety personnel and responders
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- Leverages investments in existing IT infrastructure
- Provides a single, comprehensive view of critical information from all data sources
- Provides a solution that is operational in a fraction of the time a “traditional” data integration project would take.
- Benefits from a flexible, scalable, interoperable platform capable of integrating any agency's data sources for optimal visibility and operational readiness
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